AI Agent Document Processing Cost Calculator
Estimate per-page and monthly cost for document extraction, OCR, classification, and summarization across cloud APIs and local GPU stacks.
Scenario presets
Document volume & complexity
Estimates are directional. Last updated: 2026-07-07. See notes.
Cheapest cloud provider
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Cloud cost / month
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Local cost / month
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Cost per page
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Provider cost comparison
| Provider | Best for | Monthly cost | Cost / 1k pages |
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Local GPU throughput
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Local electricity / month
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Local hardware amortized / month
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Verdict
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Frequently asked questions
What does this calculator estimate?
It estimates the monthly cost to process documents with an AI agent, including LLM tokens, vision/OCR calls, human review labor, and (for the local route) GPU hardware and electricity cost.
How are input/output tokens calculated?
Each complexity tier has average tokens per page. Total tokens = pages per month × tokens per page, plus classification overhead and vision API calls for pages that need OCR.
When is the local GPU route cheaper?
Local usually wins at very high page volumes or when documents contain sensitive data that can't leave your network. Cloud wins at lower volume, fast setup, and built-in multimodal models.
What is the review rate?
The percentage of pages that still need a human to check, correct, or approve the AI output. Review cost is added to both cloud and local routes.
Does this include OCR cost?
OCR is modeled as a percentage of pages requiring vision API calls (cloud) or local OCR+LLM time (local). Azure Document Intelligence has a per-page document-intelligence fee built into the tool-call premium.
Which provider is best for contracts or long documents?
Anthropic Claude 3.5 Sonnet and Google Gemini 1.5 Pro are strong for long-context reasoning. GPT-4o-mini and Gemini Flash are usually cheapest for simple classification.
Cost estimates are directional. Cloud provider prices change frequently and do not include storage, egress, or human QA overhead. Local route assumes you already own a compatible GPU.